Design, analysis and performance evaluation of a hand gesture platform for navigation

Megalingam, Rajesh Kannan; Rangan, Venkat; Veliyara, Pranav Sreedharan; Krishna, Rithun Raj; Prabhu, Raghavendra; Katoch, R; Koppaka, Ganesh Sai Apuroop; Sankaran, Ravi

doi:10.3233/thc-181294

Cited by 8 publications

(4 citation statements)

References 26 publications

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“…The Mobile Application Rating Scale (MARS), which was cocreated and developed by 13 young scholars, was used in this study [ 17 , 18 , 35 , 36 ]. The qualitative and quantitative data regarding the quality of the app were obtained.…”

Section: Methodsmentioning

confidence: 99%

“…This relieves the workload of the caregivers and reduces the psychological negative impact of demented patients [ 17 ]. The real-time locating system (RTLS) is a technology that helps caregivers to monitor and track the movements of patients [ 18 , 19 ]. In addition, cutting-edge technologies including 6G, artificial intelligence, wearable devices, and mobile applications are studied for dementia care [ 20 , 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

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A Survey of Mobile Apps for the Care Management of Patients with Dementia

Kuo

Chang

2022

Healthcare

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Objective: Dementia is a progressive neurocognitive disorder that currently affects approximately 50 million people globally and causes a heavy burden for their families and societies. This study analyzed mobile apps for dementia care in different languages and during the COVID-19 pandemic. Methods: We searched PubMed, Cochrane Collaboration Central Register of Con-trolled Clinical Trials, Cochrane Systematic Reviews, Google Play Store, Apple App Store, and Huawei App Store for mobile applications for dementia care. The Mobile Application Rating Scale (MARS) was used to assess the quality of applications. Results: We included 99 apps for dementia care. No significant difference in MARS scores was noted between the two language apps (Overall MARS: English: 3.576 ± 0.580, Chinese: 3.569 ± 0.746, p = 0.962). In the subscale analysis, English apps had higher scores of perceived impact than Chinese apps but these were not significant (2.654 ± 1.372 vs. 2.000 ± 1.057, p = 0.061). (2) Applications during the COVID-19 pandemic had higher MARS scores than those before the COVID-19 pandemic but these were not significant (during the COVID-19 pandemic: 3.722 ± 0.416; before: 3.699 ± 0.615, p = 0.299). In the sub-scale analysis, apps during the COVID-19 pandemic had higher scores of engagement than apps before the COVID-19 pandemic but these were not significant (3.117 ± 0.594 vs. 2.698 ± 0.716, p = 0.068). Conclusions: Our results revealed that there is a minor but nonsignificant difference between different languages and during the COVID-19 pandemic. Further cooperation among dementia professionals, technology experts, and caregivers is warranted to provide evidence-based and user-friendly information to meet the needs of users.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Survey of Mobile Apps for the Care Management of Patients with Dementia

Kuo

Chang

2022

Healthcare

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“…The research study [41] addresses the challenge of manual map requests for navigation assistance in virtual reality (VR), impacting user experience. There are other applications and approaches for people with speech issues like that of using Electro Oculography (EOG) [42], hand gestures [2,[43][44][45][46] brain computer interface (BCI) [7,[47][48][49] for control of devices but not for communicating with others.…”

Section: Related Workmentioning

confidence: 99%

“…Augmentative and Alternative Communication (AAC) is a boon to people with speech or language problems [1]. AAC supports many modes of communication that can be hand gesture based [2], eye gesture based [3], eye blinks [4], tongue [5], head [6], Brain Control Interface (BCI) [7] etc. But all these modes of communication are not useful for all users.…”

Section: Introductionmentioning

confidence: 99%

Netravaad: Interactive Eye Based Communication System for People With Speech Issues

Kannan Megalingam,

Kuttankulangara Manoharan,

Riju

et al. 2024

IEEE Access

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People who have speech disability due to apahsia caused by stroke, head injury or brain tumor, amyotrophic lateral sclerosis, cerebral palsy, locked-in syndrome or other motor impairments can use augmentative and alternative communication (AAC) for expressing their mind. Communication based on eye movements is very common for these people. Current systems based on eye gestures or eye tracking are very expensive, require re-calibration very often, slower in operation and might need a human interpreter in many cases. To overcome these limitations, we propose Netravaad, a communication system for people with speech disability to use their eyes to create signs and speak through eyes. Through the eye sign language Netravaani, the user can speak English language using eye signs. These eye signs are captured by a low-cost USB camera which are converted to a word, a phrase, a complete sentence, or even multiple sentences using the Sarani algorithm. The text thus created is displayed on the screen and converted to speech to play the audio via speaker making this interactive multi-modal interface for the benefit of the users. Predictive text feature is implemented to reduce the effort of the users in creating signs for all characters in a word. In addition, the need for human interpreters can be eliminated. Thus, the user can communicate to the caretaker, physician or relative through eyes with a feeling that is same as speaking via mouth. The tests conducted with volunteers from different age groups suggest that, on average, the system achieves an accuracy of 91%, 100%, and 93% in detecting alphabets, words, and numbers, respectively, among individuals aged 26 to 35 years. These findings underscore the robustness of the system, indicating its potential to provide significant benefits to the community of individuals with speech disabilities.

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